An Efficient Convolutional Denoising Autoencoder-Based BDS NLOS Detection Method in Urban Forest Environments.

The BeiDou Navigation Satellite System (BDS) provides real-time absolute location services to users around the world and plays a key role in the rapidly evolving field of autonomous driving. In complex urban environments, the positioning accuracy of BDS often suffers from large deviations due to non-line-of-sight (NLOS) signals. Deep learning (DL) methods have shown strong capabilities in detecting complex and variable NLOS signals. However, these methods still suffer from the following limitations. On the one hand, supervised learning methods require labeled samples for learning, which inevitably encounters the bottleneck of difficulty in constructing databases with a large number of labels. On the other hand, the collected data tend to have varying degrees of noise, leading to low accuracy and poor generalization performance of the detection model, especially when the environment around the receiver changes. In this article, we propose a novel deep neural architecture named convolutional denoising autoencoder network (CDAENet) to detect NLOS in urban forest environments. Specifically, we first design a denoising autoencoder based on unsupervised DL to reduce the long time series signal dimension and extract the deep features of the data. Meanwhile, denoising autoencoders improve the model's robustness in identifying noisy data by introducing a certain amount of noise into the input data. Then, an MLP algorithm is used to identify the non-linearity of the BDS signal. Finally, the performance of the proposed CDAENet model is validated on a real urban forest dataset. The experimental results show that the satellite detection accuracy of our proposed algorithm is more than 95%, which is about an 8% improvement over existing machine-learning-based methods and about 3% improvement over deep-learning-based approaches.

High-Accuracy Phase Frequency Detection Technology Based on BDS Time and Frequency Signals.

For the time and frequency signals of Beidou satellites, a high-accuracy phase frequency detection technology based on phase group synchronization is proposed. Using the Beidou receiver and satellite signals as the frequency standard and the measured signals, respectively. The Beidou receiver and the satellite signals are sent to the phase coincidence detector of the different frequencies to generate a phase coincidence point pulse, which is sent to the different frequency phase detector as a control signal to generate the phase differences between the Beidou receiver and satellite signals, and then complete the high-accuracy phase synchronization between the Beidou receiver and satellite signals. Experimental results show that when the delay resolution reaches ps level, the phase synchronization accuracy of the system can reach 10 ps, which has the characteristics of small phase noise, low development cost, simple circuit structure, and high synchronization accuracy compared with the traditional phase synchronization technologies. Therefore, it would be widely used in satellite positioning, astrometry, precision navigation, aerospace, satellite launch, power transmission, communications, radar, and other high-tech fields.

High Precision Positioning and Rotation Angle Estimation of a Flatbed Truck Based on BDS and Vision.

Centimeter-level localization and precise rotation angle estimation for flatbed trucks pose significant challenges in unmanned forklift automated loading scenarios. To address this issue, the study proposed a method for high-precision positioning and rotation angle estimation of flatbed trucks using the BeiDou Navigation Satellite System (BDS) and vision technology. First, an unmanned forklift equipped with a Time-of-Flight (ToF) camera and a dual-antenna mobile receiver for BDS positioning collected depth images and localization data near the front and rear endpoints of the flatbed. The Deep Dual-Resolution Network-23-slim (DDRNet-23-slim) model was used to segment the flatbed from the depth image and extract the straight lines at the edges of the flatbed using the Hough transform. The algorithm then computed the set of intersection points of the lines. A neighborhood feature vector was designed to identify the endpoint of a flatbed from a set of intersection points using feature screening. Finally, the relative coordinates of the endpoints were converted to a customized forklift navigation coordinate system by BDS positioning. A rotation angle estimation was then performed using the endpoints at the front and rear. Experiments showed that the endpoint positioning error was less than 3 cm, and the rotation angle estimation error was less than 0.3°, which verified the validity and reliability of the method.

High-Precision Positioning and Rotation Angle Estimation for a Target Pallet Based on BeiDou Navigation Satellite System and Vision.

In outdoor unmanned forklift unloading scenarios, pallet detection and localization face challenges posed by uncontrollable lighting conditions. Furthermore, the stacking and close arrangement of pallets also increase the difficulty of positioning a target pallet. To solve these problems, a method for high-precision positioning and rotation angle estimation for a target pallet using the BeiDou Navigation Satellite System (BDS) and vision is proposed. Deep dual-resolution networks (DDRNets) are used to segment the pallet from depth images and RGB images. Then, keypoints for calculating the position and rotation angle are extracted and further combined with the 3D point cloud data to achieve accurate pallet positioning. Constraining the pixel coordinates and depth coordinates of the center point of the pallet and setting the priority of the pallet according to the unloading direction allow the target pallet to be identified from multiple pallets. The positioning of the target pallet in the forklift navigation coordinate system is achieved by integrating BDS positioning data through coordinate transformation. This method is robust in response to lighting influences and can accurately locate the target pallet. The experimental results show that the pallet positioning error is less than 20 mm, and the rotation angle error is less than 0.37°, which meets the accuracy requirements for automated forklift operations.

Synthesis of Solketal Catalyzed by Acid-Modified Pyrolytic Carbon Black from Waste Tires.

Solketal, a widely used glycerol-derived solvent, can be efficiently synthesized through heterogeneous catalysis, thus avoiding the significant product losses typically encountered with aqueous work-up in homogeneous catalysis. This study explores the catalytic synthesis of solketal using solid acid catalysts derived from recovered carbon blacks (rCBs), which are obtained through the pyrolysis of end-of-life tires. This was further converted into solid acid catalysts through the introduction of acidic functional groups using concentrated H2SO4 or 4-benzenediazonium sulfonate (BDS) as sulfonating agents. Additionally, post-pyrolytic rCB treated with glucose and subsequently sulfonated with sulfuric acid was also prepared. Comprehensive characterization of the initial and modified rCBs was performed using techniques such as elemental analysis, powder X-ray diffraction, thermogravimetric analysis, a back titration method, and both scanning and transmission electron microscopy, along with X-ray photoelectron spectroscopy. The catalytic performance of these samples was evaluated through the batch mode glycerol acetalization to produce solketal. The modified rCBs exhibited substantial catalytic activity, achieving high glycerol conversions (approximately 90%) and high solketal selectivity (around 95%) within 30 min at 40 °C. This notable activity was attributed to the presence of -SO3H groups on the surface of the functionalized rCBs. Reusability tests indicated that only rCBs modified with glucose demonstrated acceptable catalytic stability in subsequent acetalization cycles. The findings underscore the potential of utilizing end-of-life tires to produce effective acid catalysts for glycerol valorization processes.

Cognitive impairment and health-related quality of life amongst older Australians: evidence from a longitudinal investigation.

INTRODUCTION: Australia's population is steadily growing older, with older persons expected to make up over 20% of the population by 2066. Ageing is strongly associated with a significant drop in cognitive ability, ranging from mild cognitive impairment to severe cognitive impairment (dementia). This study examined the association between cognitive impairment and health-related quality of life (HRQoL) in older Australians. METHODS: Two waves of longitudinal data from the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey were utilised, with the age cut-off for older Australians defined as above 50. The final analysis included 10,737 person-year observations from 6892 unique individuals between 2012 and 2016. This study utilised the Backwards Digit Span (BDS) test and Symbol Digit Modalities test (SDMT) to assess cognitive function. HRQoL was measured using the physical and mental component summary scores of the SF-36 Health Survey (PCS and MCS). Additionally, HRQoL was measured using health state utility values (SF-6D score). A longitudinal random-effects GLS regression model was used to analyse the association between cognitive impairment and HRQoL. RESULTS: This study found that approximately 89% of Australian adults aged 50 or older had no cognitive impairment, 10.16% had moderate cognitive impairment, and 0.72% had severe cognitive impairment. This study also found that moderate and severe cognitive impairment were both negatively associated with HRQoL. Older Australians with moderate cognitive impairment scored worse on the PCS (ß = - 1.765, SE = 0.317), MCS (ß = - 1.612, SE = 0.326), and SF-6D (ß = - 0.024, SE = 0.004) than peers without cognitive impairment given other covariates reference categories remain constant. Older adults experiencing severe cognitive had lower PCS (ß = - 3.560, SE = 1.103), and SF-6D (ß = - 0.034, SE = 0.012) scores compared to their counterparts with no cognitive impairment given other covariates reference categories remain constant. CONCLUSION: We found evidence that HRQoL is negatively associated with cognitive impairment. Our findings will be beneficial for the future cost-effectiveness intervention targeted at reducing cognitive impairment since it provides information on the disutility associated with moderate and severe cognitive impairment.

Algorithms Research and Precision Comparison of Different Frequency Combinations of BDS-3\GPS\Galileo for Precise Point Positioning in Asia-Pacific Region.

With the continuous construction and development of the BeiDou navigation satellite system (BDS), its positioning performance is constantly being improved. In this study, the positioning performance of different frequency combinations of BDS-3/GPS/Galileo in the Asia-Pacific region was investigated. The precision products of Wuhan University and the observation data of nine MGEX stations were selected to compare and analyze the B1I\B1C\B2a\B3I and L1\E1 pseudo-range Standard Point Positioning (SPP) and B1IB2a\B1IB3I\B1CB2a\B1CB3I\B2aB3I\L1L2\E1E5a precise point positioning (PPP) performance, while B1I\B3I\L1 SPP and B1IB3I PPP were investigated using BDS-2 with QZSS supplemented with BDS-3 and GPS. The experimental results showed that the positioning precision of BDS-3/GPS/Galileo SPP was in the order of B1C > E1 > L1 > B1I > B3I > B2a, and it was not significantly improved after BDS-2 and QZSS were added. Moreover, for the PPP of different frequency combinations, the convergence speed was in the order of L1L2 > B1IB3I > E1E5a > B1CB3I > B1CB2a > B1IB2a > B2aB3I. After adding BDS-2, B1IB3I improved by about 11% in static mode and 27% in kinematic mode, which was similar to the L1L2 frequency combination. The positioning precision of different frequency combinations of BDS-3/GPS/Galileo was B1IB3I > B1CB3I > L1L2 > E1E5a > B1B2a > B1CB2a > B2aB3I. In static mode, after adding BDS-2, B1IB3I did not show significant improvement in the plane direction, and showed ~61% improvement in the elevation direction, and ~67% in the three-dimensional (3D) direction. In kinematic mode, after adding BDS-2, B1IB3I was improved by about 16% in the E direction, the N direction did not show significant change, it improved by ~38% in the U direction and by ~70% in the 3D direction. In general, the positioning performance of BDS-3 was slightly better than those of GPS and Galileo in the Asia-Pacific region, and it is believed that with the continuous development of BDS, its positioning performance will surely be improved further.

BDS Dual-Frequency Carrier Phase Multipath Hemispherical Map Model and Its Application in Real-Time Deformation Monitoring.

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by applying the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, we propose a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of "zero mean" and divides the appropriate grid density of GEO and IGSO/MEO, respectively, to construct a dual-frequency multipath hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multipath error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates are 1.7 mm and 4.6 mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60%, respectively. The fixed rate of ambiguity increased by 5-7%.

The Extraction and Characterization of Pseudorange Multipath Based on BDS-3 Multi-Frequency Observations.

Global Navigation Satellite System (GNSS) observations are subject to various errors during their propagation process. A reasonable correction of these errors can improve the positioning, navigation, and timing (PNT) service capability. The impact of multipaths on pseudorange observations can reach a decimeters or even meters level. However, their mechanism is complex and there is currently no universally accepted high-precision correction model. The correlation between the pseudorange multipaths (MP) of BDS-2 satellites and satellite elevation has been confirmed, while there have been fewer analyses of the MP characteristics for different frequencies of BDS-3 satellites. The broadcasting of multi-frequency observations in BDS-3 should theoretically make the extracted MP more accurate compared to traditional methods. Based on this, in this contribution, a multi-frequency MP extraction algorithm based on the least squares principle is proposed, which can simultaneously eliminate the influence of higher-order ionospheric delay. The analytical expression for only eliminating first-order ionospheric delay is successfully derived. Subsequently, the characteristics of the MPs extracted from different frequency combinations and the impact of combination noise on the extraction accuracy are discussed. The influence of second-order ionospheric delay on the MPs for each frequency under different combination noises, as well as the periodic behavior exhibited in long-term observations of the BDS-3 medium earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites, are also analyzed. Finally, the correlations between the MPs of each frequency of BDS satellite and elevation are quantitatively analyzed based on observations from 35 stations. Overall, this work has positive implications for the study of the MP characteristics of BDS-3 and subsequent modeling efforts.

A Fully Integrated Low-Power Multi-Mode RF Receiver for BDS-3/GPS.

A fully integrated low-power area-efficient receiver using a low-intermediate frequency topology for BDS-3 and GPS L1 bands is presented in this paper. Accurate localization can be achieved without requiring off-chip low-noise amplifiers. The receiver bandwidths for GPS and BDS-3 are 2 MHz and 4 MHz, respectively. Digitally assisted calibration schemes, such as RC calibration, automatic gain control, and DC offset correction are integrated to resist the effects of the process, voltage, and temperature (PVT) variations. The receiver-fabricated in a standard 55 nm CMOS technology-provides a maximum gain of 113.2 dB, a gain control range of 61 dB, and a minimum noise figure of 1.74 dB under a 1.2 V supply. The receiver, with and without the frequency synthesizer that provides the local oscillator frequency, consumes 8.7 mA and 4.8 mA, with areas of 0.73 mm2 and 0.345 mm2, respectively.

PPP/INS Tight Integration with BDS-3 PPP-B2b Service in the Urban Environment.

To provide continuous and reliable real-time precise positioning services in challenging environments and poor internet conditions, the real-time precise corrections of the BeiDou global navigation satellite system (BDS-3) PPP-B2b signal are utilized to correct the satellite orbit errors and clock offsets. In addition to this, using the complementary characteristics of the inertial navigation system (INS) and the global navigation satellite system (GNSS), a PPP-B2b/INS tight integration model is established. With observation data collected in an urban environment, the results show that PPP-B2b/INS tight integration can ensure a decimeter-level positioning accuracy; the positioning accuracies of the E, N, and U components are 0.292, 0.115, and 0.155 m, respectively, which can provide a continuous and secure position during short interruptions in the GNSS. However, there is still a gap of about 1 dm compared with the three-dimensional (3D) positioning accuracy obtained from Deutsche GeoForschungsZentrum (GFZ) real-time products, and a gap of about 2 dm compared with the GFZ post-precise products. Using a tactical inertial measurement unit (IMU), the velocimetry accuracies of the tightly integrated PPP-B2b/INS in the E, N, and U components are all about 0.3 cm/s, and the attitude accuracy of yaw is about 0.1 deg, while the pitch and roll show a superior performance of less than 0.01 deg. The accuracies of the velocity and attitude mainly depend on the performance of the IMU in the tight integration mode, and there is no significant difference between using real-time products and post products. The performance of the microelectromechanical system (MEMS) IMU and tactical IMU is also compared, and the positioning, velocimetry, and attitude determinations with the MEMS IMU are significantly worsened.

Displacement Monitoring of a Bridge Based on BDS Measurement by CEEMDAN-Adaptive Threshold Wavelet Method.

From the viewpoint of BDS bridge displacement monitoring, which is easily affected by background noise and the calculation of a fixed threshold value in the wavelet filtering algorithm, which is often related to the data length. In this paper, a data processing method of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), combined with adaptive threshold wavelet de-noising is proposed. The adaptive threshold wavelet filtering method composed of the mean and variance of wavelet coefficients of each layer is used to de-noise the BDS displacement monitoring data. CEEMDAN was used to decompose the displacement response data of the bridge to obtain the intrinsic mode function (IMF). Correlation coefficients were used to distinguish the noisy component from the effective component, and the adaptive threshold wavelet de-noising occurred on the noisy component. Finally, all IMF were restructured. The simulation experiment and the BDS displacement monitoring data of Nanmao Bridge were verified. The results demonstrated that the proposed method could effectively suppress random noise and multipath noise, and effectively obtain the real response of bridge displacement.

A new method providing complementary explanation of the blood-enriching function and mechanism of unprocessed Angelica sinensis and its four kinds of processed products based on tissue-integrated metabolomics and confirmatory analysis.

Angelica sinensis (AS) is a common Traditional Chinese Medicine used for tonifying blood in China. Unprocessed AS and its four kinds of processed products (ASs) are used to treat blood deficiency syndrome in the country. The different blood-tonifying mechanisms of ASs remain unclear. In this work, a novel method integrating metabolomics and hematological and biochemical parameters was established to provide a complementary explanation of blood supplementation mechanism of ASs. Our results revealed that different ASs exhibited various blood supplementation effect, and that AS parched with alcohol demonstrated the best blood supplementation effect. Eight metabolites from liver tissue and 12 metabolites from spleen tissue were considered to be potential biomarkers. These biomarkers were involved in four metabolic pathways. Correlation analysis results showed that l-aspartic acid and l-alanine (spleen tissue), linoleic acid, and l-cystathionine (liver tissue) exhibited a high positive or negative correlation with the aforesaid biochemical indicators. The blood-supplementation effect mechanism of ASs were related to four metabolic pathways. l-Aspartic acid and l-alanine (spleen tissue), linoleic acid, and l-cystathionine (liver tissue) were the four key metabolites associated with the blood supplementation effect of ASs. This study gives a complementary explanation of the blood supplementation effect and mechanism of action of ASs.

Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System.

Malicious botnets such as Mirai are a major threat to IoT networks regarding cyber security. The Botnet Defense System (BDS) is a network security system based on the concept of "fight fire with fire", and it uses white-hat botnets to fight against malicious botnets. However, the existing white-hat Worm Launcher of the BDS decides the number of white-hat worms, but it does not consider the white-hat worms' placement. This paper proposes a novel machine learning (ML)-based white-hat Worm Launcher for tactical response by zoning in the BDS. The concept of zoning is introduced to grasp the malicious botnet spread with bias over the IoT network. This enables the Launcher to divide the network into zones and make tactical responses for each zone. Three tactics for tactical responses for each zone are also proposed. Then, the BDS with the Launcher is modeled by using agent-oriented Petri nets, and the effect of the proposed Launcher is evaluated. The result shows that the proposed Launcher can reduce the number of infected IoT devices by about 30%.

A Modified Single-Frequency PPP Method for the Positioning and Time Transfer with BDS-3.

In this paper, time-frequency transfer and positioning experiments with signal coexistence in the BDS system were conducted using the four types of open service signals of the BDS-3 satellite (B1I, B1C, B2a, and B3I), as well as the B2I signals broadcast by the BDS-2 satellites. The experiments used the single-frequency PPP (precise point positioning) method. The experiment validated a modified version of the group and phase ionospheric correction (GRAPHIC) technique. The results demonstrate that, with a single frequency, 18 selected stations may provide positioning results accurate to within a few decimeters. The positioning accuracy of five frequencies signals is improved by 40.4%, 32.2%, 80.3%, 12.4%, and 10.3% when compared to the positioning accuracy of the same signals when using the general observation approach. Currently, the frequency stability may be as precise as dual frequencies with BDS.

Sesquiterpene Lactones Potentiate Olaparib-Induced DNA Damage in p53 Wildtype Cancer Cells.

Despite notable advances in utilising PARP inhibitor monotherapy, many cancers are not PARP inhibitor-sensitive or develop treatment resistance. In this work, we show that the two structurally-related sesquiterpene lactones, a 2-bromobenzyloxy derivative of dehydrosantonin (BdS) and alantolactone (ATL) sensitise p53 wildtype, homologous recombination-proficient cancer cells to low-dose treatment with the PARP inhibitor, olaparib. Exposure to combination treatments of olaparib with BdS or ATL induces cell-cycle changes, chromosomal instability, as well as considerable increases in nuclear area. Mechanistically, we uncover that mitotic errors likely depend on oxidative stress elicited by the electrophilic lactone warheads and olaparib-mediated PARP-trapping, culminating in replication stress. Combination treatments exhibit moderately synergistic effects on cell survival, probably attenuated by a p53-mediated, protective cell-cycle arrest in the G2 cell-cycle phase. Indeed, using a WEE1 inhibitor, AZD1775, to inhibit the G2/M cell-cycle checkpoint further decreased cell survival. Around half of all cancers diagnosed retain p53 functionality, and this proportion could be expected to increase with improved diagnostic approaches in the clinic. Utilising sublethal oxidative stress to sensitise p53 wildtype, homologous recombination-proficient cancer cells to low-dose PARP-trapping could therefore serve as the basis for future research into the treatment of cancers currently refractory to PARP inhibition.

Biological assisted organic sulfur removal from low rank indigenous coal using airlift bioreactor.

Combustion of coal create many harmful gases which effect on human health as well as on environment. The sulfur in coal limits its own use, and bio-desulfurization (BDS) shows enormous development potential and the prospects for the application of coal desulfurization. Present study highlights the bioprocess strategies for reduction of sulfur content from coal before combustion. The bioprocess involved the use of Airlift Bioreactor along with Rhodococcus sp. ATCC55309 as biocatalyst. Different nutritional and operational parameters involved to promote sulfur reduction at maximum level. The parameters were investigated are different carbon source, temperature, pH, Agitation speed, and pulp density. The impact of these parameters shows that sulfur removal can be enhanced though optimized conditions. The amount of total sulfur and organic sulfur present in coal were reduced by 33 ± 1.7% and 71 ± 1.5%, respectively, compared to untreated coal at controlled condition of various parameters are 20% (w/v) pulp density, 30 °C, 170 rpm, glucose as carbon source and pH 7. Whereas organic sulfur degrades from coal using Rhodococcus sp. ATCC55309 about 0.36 mM DBT (Di-benzothiophene) within 8 days via 4S-pathway. The maximum conversion of DBT compound into 2-HBP(2-hydroxybiphenyl) by utilizing 30 °C, 170 rpm, 20 pulp density and glucose as carbon source.

A Novel Signal Design and Performance Analysis in NavCom Based on LEO Constellation.

The mega-launch of low Earth orbit satellites (LEOs) represents a critical opportunity to integrate navigation and communication (NavCom), but first, challenges related to signal design must be overcome. This article proposes a novel signal scheme named CE-OFDM-PM. Via research on the in-band or adjacent band, it was found that the proposed signal scheme was suitable for S-band and had a wide normalized power spectrum density (PSD), high peak-to-side lobe ratio (PSR), and multiple peaks in autocorrelation. In an analysis of the simulation performance evaluation in navigation and communication, it is found that the proposed signal scheme has the potential for high accuracy, a code tracking accuracy of up to 0.85 m, a small mutual influence between the proposed signal scheme and other schemes, excellent anti-interference properties, and a better performance at both short and long distances in terms of its anti-multipath capability. Furthermore, the proposed signal scheme shows the ability to communicate between satellites and the ground and is outstanding in terms of its bit error rate (BER), CNR, and energy per bit to noise power spectral density ratio (Eb/N0). From the technical, theoretical, and application perspectives, our proposed signal scheme has potential as an alternative scheme in future BDS, PNTs, and even 5G/B5G.

A Comparative Study of BDS Triple-Frequency Ambiguity Fixing Approaches for RTK Positioning.

Concerning the triple-frequency ambiguity resolution, in principle there are three different realizations. The first one is to fix all the ambiguities of the original frequencies together. However, it is also believed that fixing the combined integer ambiguities with longer wavelength, such as extra-wide-lane (EWL), wide-lane (WL), should be advantageous. Also, it is demonstrated that fixing sequentially EWL, WL and one type of original ambiguities provides better results, as the previously fixed ambiguities increase parameters' precision for later fixings. In this paper, we undertake a comparative study of the three fixing approaches by means of experimental validation. In order to realize the three fixing approaches from the same information in terms of adjustment, we developed a processing strategy to provide fully consistent normal equations. We first generate the normal equation with the original undifferentiated carrier phase ambiguities, then map it into that with the combined and double-differenced ambiguities required by the individual approach for fixing. Four baselines of 258 m, 22 km, 47 km and 53 km are selected and processed in both static and kinematic mode using the three ambiguity-fixing approaches. Indicators including time of first fixed solution (TFFS), the correct fixing rate, positioning accuracy and RATIO are used to evaluate and investigate results. We also made a preliminary theoretical explanation of the results by looking into the decorrelation procedure of the ambiguity searching algorithm and the intermediate results. As conclusions, integrated searching of original ambiguities or combined ambiguities has almost the same fixing performance, whereas the sequential fixing of EWL, WL and B1 ambiguities overperforms the integrated searching. By the way, the third-frequency data can shorten the TFFS significantly but can hardly improve the positioning.

Performance Evaluation of Precise Point Positioning for BeiDou-3 B1c/B2a Signals in the Global Range.

With the construction and development of the BeiDou navigation satellite system (BDS), the precise point positioning (PPP) performance of the BDS is worthy of research. In this study, observational data from 17 stations around the world across 20 days are used to comprehensively evaluate the PPP performance of BDS B1c/B2a signals. For greater understanding, the results are also compared with the Global Positioning System (GPS) and BDS PPP performance of different signals and system combinations. The evaluation found root mean square (RMS) values of the static PPP in the north (N), east (E), and upward (U) components, based on the B1c/B2a frequency of BDS-3, to be 6.9 mm, 4.7 mm, and 26.6 mm, respectively. Similar to the static positioning, the RMS values of kinematic PPP in the three directions of N, E, and U are 2.6 cm, 6.0 cm, and 8.5 cm, respectively. Besides this, the static PPP of BDS-3 (B1cB2a) and BDS-2 + BDS-3 (B1IB3I) have obvious system bias. Compared with static PPP, kinematic PPP is more sensitive to the number of satellites, and the coordinate accuracy in three dimensions can be increased by 27% with the combination of GPS (L1L2) and BDS. Compared with BDS-2+BDS-3 (B1IB3I), the convergence time of BDS-3 (B1CB2a) performs better in both static and kinematic modes. The antenna model does not show a significant difference in terms of the effect of the convergence speed, though the number of satellites observed has a certain influence on the convergence time.